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ARS Home » Southeast Area » Stoneville, Mississippi » Genomics and Bioinformatics Research » Research » Research Project #438850

Research Project: Computational Biology: Studying Species of Agronomic, Ecological, and Evolutionary Importance

Location: Genomics and Bioinformatics Research

Project Number: 6066-21310-006-012-S
Project Type: Non-Assistance Cooperative Agreement

Start Date: Sep 23, 2020
End Date: Sep 22, 2024

Objective:
The Institute for Genomics, Biocomputing & Biotechnology (IGBB) at Mississippi State University (MS State) and the ARS’s Genomics & Bioinformatics Research Unit (GBRU) will continue their collaborative efforts to advance laboratory and computational biology-based study of organisms of agricultural, ecological, and/or evolutionary importance. Goals of the current project include (but are not limited to) [a] acquisition and utilization of a liquid handling system to facilitate high-throughput genotyping studies; [b] development and use of data analysis pipelines to advance microbiome and metagenomics research; [c] generation of novel computer scripts and adaptation of existing scripts for large-scale computational analyses; [d] conducting genomics, transcriptomics, proteomics, and metabolomics research on organisms of agricultural, ecological, and/or evolutionary importance; [e] advancement of gene pathway research through refinement of laboratory and computational techniques; and [f] participation in training ARS and other scientists in data analyses. The research, which will be conducted in collaboration with several ARS groups and academic scientists, will advance understanding of important organisms and their relationships to their environments.

Approach:
Pacific Bioscience (PacBio, long-read) and/or Oxford Nanopore Technologies (ONT, long-read) sequencing technologies will be used for genome sequencing. Illumina (short-read) sequencing will be used for transcriptome sequencing, genome resequencing, genotyping via double-digest restriction-site associated DNA sequencing (ddRADseq), and Hi-C sequencing. Proteomics and metabolomics data will be generated using the IGBB’s LTQ Orbitrap Velos mass spectrometer. RT-qPCR will be used to validate RNASeq-based differential gene expression results. The IGBB will utilize its supercomputing capacity and expertise to conduct data analysis and develop bioinformatics tools. Computational tools developed for this project will be tested on existing and new data sets, with laboratory support data being generated as needed. Workshops will be developed by IGBB faculty/staff to train ARS and other scientists in advanced data analysis techniques.